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As you note in 2.1, there is widespread disagreement on what "AGI" means. I note that you list several definitions which are essentially "is human equivalent". As humans can be reduced to physics, and physics can be expressed as a computer program, obviously any such definition can be achieved by a sufficiently powerful computer.
For 3.1, you assert:
"""
Now, let's observe what happens when an Al system - equipped with state-of-the-art natural language processing, sentiment analysis, and social reasoning - attempts to navigate this question. The Al begins its analysis:
• Option 1: Truthful response based on biometric data → Calculates likely negative emotional impact → Adjusts for honesty parameter → But wait, what about relationship history? → Recalculating...
• Option 2: Diplomatic deflection → Analyzing 10,000 successful deflection patterns → But tone matters → Analyzing micro-expressions needed → But timing matters → But past conversations matter → Still calculating...
• Option 3: Affectionate redirect → Processing optimal sentiment → But what IS optimal here? The goal keeps shifting → Is it honesty? Harmony? Trust? → Parameters unstable → Still calculating...
• Option n: ....
Strange, isn't it? The Al hasn't crashed. It's still running. In fact, it's generating more and more nuanced analyses. Each additional factor may open ten new considerations. It's not getting closer to an answer - it's diverging.
"""
Which AI? ChatGPT just gives an answer. Your other supposed examples have similar issues in that it looks like you've *imagined* an AI rather than having tried asking an AI to seeing what it actually does or doesn't do.
I'm not reading 47 pages to check for other similar issues.
This is an assumption that many physicists disagree with. Roger Penrose, for example.
This is obvious!, you might say — obviously we can just pick one element from each set and be done with it. But the statement that we can pick an element from each set is the axiom of choice.
Note that it's not necessarily simple to pick an element from a set. For instance, how would one pick an element from the set of uncomputable numbers? A human cannot describe said element, by definition. The axiom of choice says it's possible anyway.
In ZF without choice, you can pick an element from any non-empty set, so it actually is simple to pick an element from a set. Choice is only needed when you have an infinite number of sets to pick elements from.
While they will usually produce video on old CRTs, the video signal they generate is technically not valid. The VSync signal needs to be generated in software, and random programs are unlikely to do so correctly. Different TVs will behave differently (usually rolling on old TVs, blank on new TVs), and probably none would look like what the emulator is showing.
I tried running the game-like ROM in Stella and couldn't get it to work. It seems to depend on the startup state, which means it likely wouldn't run on an actual console.
For the overwhelming majority of programmers, assembly offers absolutely no benefit. I learned (MC6809) assembly after learning BASIC. I went on to become an embedded systems programmer in an era where compilers were still pretty expensive, and I worked for a cheapskate. I wrote an untold amount of assembly for various microcontrollers over the first 10 years of my career. I honestly can't say I got any more benefit out of than programming in C; it just made everything take so much longer.
I once, for a side gig, had to write a 16-bit long-division routine on a processor with only one 8-bit accumulator. That was the point at which I declared that I'd never write another assembly program. Luckily, by then gcc supported some smaller processors so I could switch to using Atmel AVR series.
This is exactly the kind of job I'd enjoy! A perfectly doable technical challenge with clear requirements. Some people like solving Sudoku puzzles, I like solving programming puzzles.
I guess I'm just not "the overwhelming majority of programmers".
With a Turing-Complete language, if a program runs out of memory on one machine, you can run the same code on a bigger machine without modifying it, and it can use the additional memory. With fixed-length rule 110, you need to modify the code if you want to use more memory.